Fundamentals of BI Report Testing - Module 3

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Module 3
Principles of BI Report Testing
Interactivity

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Module Outline
− Introduction to Testing Report Filters and Parameters
− Types of BI Report filters
− Testing BI Report Filters
− Testing Hierarchical Filters and Drill Downs

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Introduction to BI Report Interactivity
• Interactivity lies at the core of user engagement within BI reports, enabling users to actively engage
with data and zero in on the metrics of their greatest interest.
• Filters and prompts are interactive elements that grant users the power to customize their data
views, making them an indispensable part of the BI reporting experience.

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Understanding Filters and Prompts in BI Reports
Filters and prompts are the tools that empower users to customize their reports according to their specific
requirements.
• Adding Complexity: While these customization features enhance user experience, they can also introduce
complexity and the possibility of errors.
• Key Knowledge: It's essential to grasp the different filter options available and how they influence the visual
representation of data in reports.
• Testing Importance: Understanding these concepts is critical for crafting effective tests to validate report
results.
• Upcoming Topics: In the upcoming slides, we'll delve into various types of report filters, exploring how they
affect the presentation of data in reports
Filters and prompts are powerful customization features in BI reports, but proper understanding is vital for
effective testing and ensuring data is presented accurately.

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BI Report Interactivity Variations
Depending on the BI platform used for report creation, the way users interact with the reports can
vary.
• For instance, MicroStrategy BI Reports often prompt users to specify criteria
before generating a report, with filtering options available afterward.
• In contrast, Microsoft's Power BI doesn’t generally use prompts before
generating reports; instead, reports are hosted in workspaces or embedded in
websites, allowing users to directly access and manipulate data using slicers
within the reports.
When testing these reports, it's crucial to grasp the capabilities of the BI platform, how they align with end-user
requirements, and understand how the development team has implemented these features.

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Date Filters
Allow users to select a specific date range or time period for data analysis, such as a specific month, quarter, year,
or custom date range. Relative Date Filters provide predefined date filter options like "Today," "Last 7 Days," or
"Next Month," making it easy for users to select dynamic date ranges.

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Boolean Filters
These filters provide options like “True" or “False” allowing users to filter data based on binary choices, such as
whether a customer has made a purchase or not under the Is_Active field.

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Category Filters
Enable users to filter data based on specific categories, such as product categories, geographic regions,
departments, or customer segments.

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Multi-Select Filters
Allow users to select multiple items from a list simultaneously, which is useful for scenarios where users want to
compare or analyze several items at once.

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Numeric Filters
Allow users to filter data based on numerical criteria, such as sales above a certain threshold, inventory levels
below a specific quantity, or budget variance within a defined range.

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Text Filters
Enable users to filter data based on text criteria, such as filtering customer names that contain specific keywords or
filtering product descriptions that match certain terms.

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Geospatial Filters
Enable users to filter data based on geographic criteria, such as selecting data points within a specific region on a
map.

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Top-N Filters
Enable users to filter data to show the top or bottom N items based on a specific measure, like displaying the top
10 products by sales.

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User-Based Permission Filters
Filters data based on user-specific criteria, ensuring that each user sees only the data relevant to their role or
permissions.

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Testing Various Combinations of Filters and Parameters
Filters and parameters within BI reports often offer users a range of choices and options. Testing is essential to
ensure that all possible combinations and permutations of these options are thoroughly examined.
To provide a robust testing process, it's imperative to test not only individual filter or parameter options but also
the interactions between them. Users may combine multiple filters or parameters in unique ways to refine their
data views. Comprehensive testing seeks to cover all possible scenarios and user interactions.
Testing is crucial because it helps identify potential issues such as:
• Incorrect Data Filtering: Ensuring that selected filters and parameters correctly filter and display the relevant
data while excluding irrelevant data.
• Unexpected Behavior: Discovering any unexpected interactions or behaviors that may occur when users choose
specific combinations of filters and parameters.
• Data Consistency: Verifying that the data presented in the report remains consistent and accurate across
various combinations.

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Testing Various Combinations of Filters and Parameters
When preparing to test BI report filters and parameters it is important to understand the specific objectives of the
filters.
• Identify Filter Types: Identify the different types of filters in the report, such as date filters, category filters, or user-
defined filters.
• Crafting Test Cases: Each filter type warrants a set of dedicated test cases. For each test case:
o Specify Input Parameters: Define the filter parameters, including values, ranges, or categories.
o Expected Outcomes: Clearly state what data is expected to be displayed or hidden based on the filter selection.
o Boundary Testing: Include test cases for edge scenarios, such as minimum and maximum values, null inputs,
and exceptional conditions.
o Performance Testing: Assess filter performance with varying dataset sizes and complexities.
o Interactivity Testing: Verify that filters are user-friendly, easy to select, and responsive to user input.
o Data Integrity Testing: Ensure that filters do not compromise data integrity. The data displayed should
accurately reflect the filter selections.

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Cross-Filtering
A "cross-filter" report typically refers to a report or analysis where data from one aspect or dimension is filtered
based on the selection made in another dimension.
For example, in a sales report, you might have two dimensions: time (e.g., months) and product categories. If you
select a specific month, a cross-filtered report would adjust to display only the data related to that particular
month, such as sales figures for different product categories during that time period.
Similarly, if you select a specific product category, the report will adapt to show data for that category across
various months.

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Hierarchical Filters and Drill-Downs
• Drill-downs are a powerful feature in BI reports that enable users to delve
deeper into data hierarchy. They allow users to navigate from summarized
or high-level information to more detailed or granular data.
• Typically, a BI report will present data in a hierarchical structure. When
users click on a summarized data point, like a total or category, drill-downs
reveal a breakdown of that data, often with further details and
subcategories.
• Drill-downs are initiated by user interactions, such as clicking on data
points, icons, or specific elements within a report. These interactions
trigger the report to adapt and display more refined information.

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Drill-down/Hierarchical Filters
Enable users to navigate through hierarchical data structures, such as organizational charts or product hierarchies,
to filter data at various levels of granularity.

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Testing Drill-Downs in BI Reports
Accurate and responsive drill-downs are vital for users to explore data effectively. Testing ensures that this
functionality works as expected, enhancing the value of BI reports. When testing drill-downs in BI reports,
consider the following steps:
• Initial Testing: Start with basic tests to ensure drill-downs function as intended. Click on summary data
points and confirm that detailed data is displayed.
• Data Accuracy: Verify that drill-downs maintain data accuracy, with no discrepancies or anomalies, as you
navigate through different levels.
• Performance Testing: Assess how the report performs during drill-downs, especially with large datasets or
complex calculations. Ensure it remains responsive.
• User Experience: Evaluate the user experience by testing the intuitiveness of drill-down interactions. Ensure
that they are user-friendly and responsive.

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Summary
• Interactivity lies at the core of user engagement within BI reports, enabling users to actively engage with data
and zero in on the metrics of their greatest interest.
• Filters and prompts are powerful customization features in BI reports, but their proper understanding is vital
for effective testing and ensuring data is presented accurately.
• The type of filter will impact the data displayed in the BI Report:
• A "cross-filter" report typically refers to a report or analysis where data from one aspect or dimension is
filtered based on the selection made in another dimension.
• Drill-downs are a powerful feature in BI reports that enable users to delve deeper into data hierarchy. They
allow users to navigate from summarized or high-level information to more detailed or granular data.
 Date Filter
 Boolean Filter
 Category Filter
 Multi Select Filter
 Numeric Filter
 Text Filter
 Geospatial Filter
 Top-N Filter
 User-Based Permission Filter
 Drill-down/Hierarchical Filters

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